In this dissertation we pose the problem of evaluating robot performance
in a multiple criteria framework. Specifically, we propose a new
evaluation methodology for mobile robots navigating in terrain cluttered
with obstacles. The technique relies on a combination of multiple
statistical criteria. We present a comparative performance analysis of three
physical robots to which the evaluation functions were applied. One of
the systems constructed for the experiments is a novel quadruped robot; the
other two are four wheeled systems. Physics based dynamic simulations
of the systems were written, validated, and subjected to the same evaluation
functions as the real robots. Nearly 1000 runs of the simulated traverses were
performed to obtain a high degree of confidence. Statistics
of these runs show that the simulations were good representations of the
actual systems. Further, we present sensitivity studies that measure the
effects of small parameter changes on the overall system performance. The
simulations were also used to study the effects of scale on the mobility
metrics. For the navigation task under study we conclude that the robot width
and ground clearance are crucial parameters that affect the mobility
performance significantly. We also show that the proposed metrics partition
the evaluation space in a meaningful way. A diffusion based model was built
which predicts robot mobility successfully. The dissertation concludes with a
discussion of alternative metrics, alternative techniques to scalarize what
is inherently a multidimensional evaluation problem and other directions for
future research.